Senior Data Engineer (Canada) in Canada Creek, Nova Scotia at Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer based in Canada.

This role offers the opportunity to design and scale a modern data platform supporting high-volume financial technology systems.
You will build reliable data infrastructure capable of processing hundreds of millions of events daily while enabling smarter business decisions.
Working within a fully distributed engineering team, you will contribute to architecture, data pipelines, and scalable solutions across the organization.
The position combines deep technical expertise with collaboration across product, operations, marketing, and business teams.
You will help shape data engineering practices by leveraging cloud technologies, open-source tools, and modern data architectures.
This is an ideal opportunity for an experienced data engineer passionate about building high-performance platforms in a fast-growing environment.

The Senior Data Engineer will design, develop, and maintain scalable data infrastructure while ensuring reliable data flows, efficient processing, and strong platform performance.

• Design and implement forward and reverse ETL patterns to deliver trusted data solutions to internal and external stakeholders.
• Develop scalable transformation frameworks that support analytics, reporting, and business intelligence needs across multiple teams.
• Expand and maintain a modern data lakehouse architecture, ensuring scalability, reliability, and performance as data volumes continue to grow.
• Build and optimize batch and streaming data ingestion pipelines across multiple systems and data sources.
• Collaborate with product, sales, marketing, and operations teams to understand data requirements and deliver effective solutions.
• Manage production systems, troubleshoot issues, and ensure timely resolution of data platform challenges.
• Improve data experimentation, cataloging, monitoring, and alerting capabilities.
• Establish reliable engineering practices around data quality, automation, and platform scalability.
• Contribute to architecture decisions involving distributed systems, storage solutions, and query optimization.
• Support the evolution of cloud-based data infrastructure using modern engineering approaches.

The ideal candidate is a highly experienced data engineering professional with strong expertise in designing distributed systems, cloud-native platforms, and large-scale data processing solutions.

• 7+ years of experience in data engineering, including at least 2 years building scalable, low-latency data platforms processing more than 100 million events per day.
• Strong programming experience with at least one programming language, with advanced proficiency in Python and SQL.
• Hands-on experience with cloud-native technologies including Docker, Kubernetes, and Helm.
• Strong experience with relational databases and object storage technologies such as Apache Iceberg.
• Proven experience with Google Cloud Platform data services, including tools such as Composer, Dataproc, and Datastream.
• Experience designing scalable transformation layers using SQL-based modeling frameworks such as dbt.
• Experience with ETL orchestration tools and frameworks such as Apache Airflow and Airbyte.
• Production experience with streaming platforms such as Kafka.
• Knowledge of infrastructure, DevOps practices, and Infrastructure as Code tools such as Terraform.
• Deep understanding of distributed systems, storage architectures, transactions, and query processing.
• Experience working with open-source distributed query engines such as Trino (formerly PrestoSQL).
• Ability to work effectively in a fast-paced environment and adapt solutions based on evolving business needs.
• Strong problem-solving skills with a focus on reliability, scalability, and technical excellence.

• Competitive salary package and stock options.
• Comprehensive health benefits.
• Fully remote work environment with a globally distributed team.
• One-time home office setup allowance of USD $500.
• Monthly stipend of USD $150 through a company expense card.
• Opportunity to work on large-scale data infrastructure and innovative financial technology solutions.
• Collaborative culture focused on ownership, curiosity, and continuous improvement.